Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-1409-2024
https://doi.org/10.5194/gmd-17-1409-2024
Development and technical paper
 | 
16 Feb 2024
Development and technical paper |  | 16 Feb 2024

Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 2: A semi-discrete error analysis framework for assessing coupling schemes

Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui

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Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 1: Dust budget analyses and the impacts of a revised coupling scheme
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024,https://doi.org/10.5194/gmd-17-1387-2024, 2024
Short summary

Cited articles

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Caya, A., Laprise, R., and Zwack, P.: Consequences of Using the Splitting Method for Implementing Physical Forcings in a Semi-Implicit Semi-Lagrangian Model, Mon. Weather Rev., 126, 1707–1713, https://doi.org/10.1175/1520-0493(1998)126<1707:COUTSM>2.0.CO;2, 1998. a
Donahue, A. S. and Caldwell, P. M.: Performance and Accuracy Implications of Parallel Split Physics-Dynamics Coupling in the Energy Exascale Earth System Atmosphere Model, J. Adv. Model. Earth Sy., 12, e2020MS002080, https://doi.org/10.1029/2020MS002080, 2020. a
Dubal, M., Wood, N., and Staniforth, A.: Analysis of Parallel versus Sequential Splittings for Time-Stepping Physical Parameterizations, Mon. Weather Rev., 132, 121–132, https://doi.org/10.1175/1520-0493(2004)131<0121:AOPVSS>2.0.CO;2, 2004. a
Dubal, M., Wood, N., and Staniforth, A.: Mixed Parallel-Sequential-Split Schemes for Time-Stepping Multiple Physical Parameterizations, Mon. Weather Rev., 133, 989–1002, https://doi.org/10.1175/MWR2893.1, 2005. a
Short summary
Generally speaking, accurate climate simulation requires an accurate evolution of the underlying mathematical equations on large computers. The equations are typically formulated and evolved in process groups. Process coupling refers to how the evolution of each group is combined with that of other groups to evolve the full set of equations for the whole atmosphere. This work presents a mathematical framework to evaluate methods without the need to first implement the methods.
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